Open AccessData‐driven‐based event‐triggered tracking control for non‐linear systems with unknown disturbance
Author(s) -
Li HaiFeng,
Wang YingChun,
Zhang HuaGuang
Publication year - 2019
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2019.0051
Subject(s) - control theory (sociology) , disturbance (geology) , computer science , controller (irrigation) , estimator , bounded function , tracking error , compensation (psychology) , tracking (education) , control engineering , control (management) , mathematics , engineering , artificial intelligence , psychology , paleontology , mathematical analysis , pedagogy , biology , statistics , psychoanalysis , agronomy
A novel event‐triggered model‐free adaptive tracking control problem is studied for non‐linear systems with unknown bounded disturbance. A general dynamic linearisation model framework with disturbance input is developed and event‐triggered‐based model‐free adaptive control algorithm is designed by using pseudo‐partial derivatives method and input/output measurement data. Owing to the existence of unknown disturbance, a disturbance estimator is designed based on the optimisation criterion technique. Then, a new event‐triggering mechanism with dead‐zone operator is designed to improve the utility of network communication resources without Zeno phenomenon. Then, an observer‐based controller with disturbance compensation is developed, such that the tracking error between the system output and desired output signal converges to a small residual set around the origin. Finally, two simulation examples are provided to show the effectiveness and practicability of the proposed approach.